Rapid host response to an infection with Coronavirus. Study of transcriptional responses with Porcine Epidemic Diarrhea Virus

  1. Wei Hou
  2. Fei Liu
  3. Wim H.M. van der Poel
  4. Marcel M. Hulst

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Abstract

The transcriptional response in Vero cells (ATCC ® CCL-81) infected with the coronavirus Porcine Epidemic Diarrhea Virus (PEDV) was measured by RNAseq analysis 4 and 6 hours after infection. Differential expressed genes (DEGs) in PEDV infected cells were compared to DEGs responding in Vero cells infected with Mammalian Orthoreovirus (MRV). Functional analysis of MRV and PEDV DEGs showed that MRV increased the expression level of several cytokines and chemokines (e.g. IL6, CXCL10, IL1A, CXCL8 [alias IL8]) and antiviral genes (e.g. IFI44, IFIT1, MX1, OASL), whereas for PEDV no enhanced expression was observed for these “hallmark” antiviral and immune effector genes. Pathway and Gene Ontology “enrichment analysis” revealed that PEDV infection did not stimulate expression of genes able to activate an acquired immune response, whereas MRV did so within 6h. Instead, PEDV down-regulated the expression of a set of zinc finger proteins with putative antiviral activity and enhanced the expression of the transmembrane serine protease gene TMPRSS13 (alias MSPL) to support its own infection by virus-cell membrane fusion (Shi et al, 2017, Viruses, 9(5):114). PEDV also down-regulated expression of Ectodysplasin A, a cytokine of the TNF-family able to activate the canonical NFKB-pathway responsible for transcription of inflammatory genes like IL1B, TNF, CXCL8 and PTGS2. The only 2 cytokine genes found up-regulated by PEDV were Cardiotrophin-1, an IL6-type cytokine with pleiotropic functions on different tissues and types of cells, and Endothelin 2, a neuroactive peptide with vasoconstrictive properties. Furthermore, by comprehensive datamining in biological and chemical databases and consulting related literature we identified sets of PEDV-response genes with potential to influence i) the metabolism of biogenic amines (e.g. histamine), ii) the formation of cilia and “synaptic clefts” between cells, iii) epithelial mucus production, iv) platelets activation, and v) physiological processes in the body regulated by androgenic hormones (like blood pressure, salt/water balance and energy homeostasis). The information in this study describing a “very early” response of epithelial cells to an infection with a coronavirus may provide pharmacologists, immunological and medical specialists additional insights in the underlying mechanisms of coronavirus associated severe clinical symptoms including those induced by SARS-CoV-2. This may help them to fine-tune therapeutic treatments and apply specific approved drugs to treat COVID-19 patients.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.28.224576: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. ScreenIT

    SciScore for 10.1101/2020.07.28.224576: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    For PEDV and corresponding mockinfected cells, 10 µg/ml of trypsin in serum-free medium was used to facilitate infection of Vero cells during the whole experiment.
    Vero
    suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059
    Software and Algorithms
    SentencesResources
    After accessing the NCBI, Panther or KEGG databases for human orthologs, not annotated Cercopithecus aethiops DEGs were annotated with an HUGO official gene symbols (http://www.genenames.org).
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    http://www.genenames.org
    suggested: (HGNC, RRID:SCR_002827)
    Sets of PEDV and MRV DEGs were analyzed using the GSEA program GeneAnalytics (LifeMap Sciences, Inc.) and pathways (for MRV and PEDV), GO-terms (not for MRV), and associations with compounds/drugs (not for MRV) with a high or medium score (p-value <0.05) were retrieved and listed in 3 separate sheets in supplementary file 3 (sheets “MRV-PEDV pathways”, “PEDV G0-terms” and “PEDV Compounds”).
    GSEA
    suggested: (SeqGSEA, RRID:SCR_005724)
    Subcellular locations of genes/proteins were retrieved from UniProtKB/Swiss-Prot. data provided in the GeneCards reports of these genes/proteins.
    GeneCards
    suggested: (GeneCards, RRID:SCR_002773)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: We did not find any issues relating to colormaps.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  3. ScreenIT

    SciScore for 10.1101/2020.07.28.224576: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variableAlso disease incidence in adult males is significantly higher than in females of the same age.Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Somatic mutations in the gene coding for the essential chaperone of C1GALT1 (C1GALT1C1), causes Tn polyagglutination syndrome (https://omim.org/entry/300622), a disorder caused by binding of natural anti-Tn antibodies to the Tn-antigen expressed on the surface of erythrocytes and other blood cells (including platelets and leukocytes).
    C1GALT1C1
    suggested: None
          <div style="margin-bottom:8px">
        <div><b>anti-Tn</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;text-align:center; padding-top:4px;" colspan="2"><b>Experimental Models: Cell Lines</b></td></tr><tr><td style="min-width:100px;text=align:center"><i>Sentences</i></td><td style="min-width:100px;text-align:center"><i>Resources</i></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In a recent study EDN2 gene expression was also up-regulated in alveolar basal epithelial cell line A549 in response to SARSCoV-2 infection (21: Blanco-Melo et al. 2020, see also below).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>A549</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">We were able to infect the majority of Vero cells (>50%) with PEDV and MRV synchronically.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Vero</b></div>
        <div>suggested: CLS Cat# 605372/p622_VERO, <a href="https://scicrunch.org/resources/Any/search?q=CVCL_0059">CVCL_0059</a></div>
      </div>
    </td></tr><tr><td style="min-width:100px;text-align:center; padding-top:4px;" colspan="2"><b>Software and Algorithms</b></td></tr><tr><td style="min-width:100px;text=align:center"><i>Sentences</i></td><td style="min-width:100px;text-align:center"><i>Resources</i></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After accessing the NCBI, Panther or KEGG databases for human orthologs, not annotated Cercopithecus aethiops DEGs were annotated with an HUGO official gene symbols (http://www.genenames.org).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>KEGG</b></div>
        <div>suggested: (KEGG, <a href="https://scicrunch.org/resources/Any/search?q=SCR_012773">SCR_012773</a>)</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>http://www.genenames.org</b></div>
        <div>suggested: (HGNC, <a href="https://scicrunch.org/resources/Any/search?q=SCR_002827">SCR_002827</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In a separate sheet “PEDV-DEGs functional info” all 266 individual DEGs regulated by PEDV at 4 and 6 h.p.i. are presented with their FC, information about their function and the types of human cells in which expression of the gene is relatively high compared to other human cells (retrieved from the “Primary Cell Atlas” dataset of BioGPS: http://biogps.org/).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>BioGPS</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>http://biogps.org/</b></div>
        <div>suggested: (BioGPS: The Gene Portal Hub, <a href="https://scicrunch.org/resources/Any/search?q=SCR_006433">SCR_006433</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In all results paragraphs beneath information about the biological function of DEGs was retrieved by consulting the “GeneCards” (Weizmann Institute of Science: https://www.genecards.org/) and NCBI Gene reports (Entrez Gene: https://www.ncbi.nlm.nih.gov/gene/), and literature linked to these reports (for references about these biological functions of genes/proteins we refer to publications cited in these reports: “GeneCards” weblinks are provided in supplementary file 3)</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Entrez Gene</b></div>
        <div>suggested: (Entrez Gene, <a href="https://scicrunch.org/resources/Any/search?q=SCR_002473">SCR_002473</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sets of PEDV and MRV DEGs were analyzed using the GSEA program GeneAnalytics (LifeMap Sciences, Inc.) and pathways (for MRV and PEDV), GO-terms (not for MRV), and associations with compounds/drugs (not for MRV) with a high or medium score (p-value <0.05) were retrieved and listed in 3 separate sheets in supplementary file 3 (sheets “MRV-PEDV pathways”, “PEDV G0-terms” and “PEDV Compounds”).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>GSEA</b></div>
        <div>suggested: (SeqGSEA, <a href="https://scicrunch.org/resources/Any/search?q=SCR_005724">SCR_005724</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">PEDV DEGs matching the terms “Cilia” and “Synaptic cleft” retrieved form the genotyping program VarElect were further examined by consulting functional information in the NCBI Gene and GeneCards reports in order to evaluate their association with these processes (see supplementary file 3, sheet “Cilia and Synaptic cleft”).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>NCBI Gene</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>Synaptic cleft”</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Subcellular locations of genes/proteins were retrieved from UniProtKB/Swiss-Prot. data provided in the GeneCards reports of these genes/proteins.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>GeneCards</b></div>
        <div>suggested: (GeneCards, <a href="https://scicrunch.org/resources/Any/search?q=SCR_002773">SCR_002773</a>)</div>
      </div>
    </td></tr></table>

    Data from additional tools added to each annotation on a weekly basis.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.07.28.224576v1 on bioRxiv